In industrial simulation workflows, finite element tools are used to understand the electromagnetic behavior of electrical machines and produce an optimal design solution. These tools take plenty of time to evaluate one single electromagnetic design. This research deals with the study of different deep learning approaches for the generation of optimal electrical machine design. It aims to reduce cost and simulation time in the process.